AI
Hybrid Search: Combining BM25 and Vector Similarity
Why pure vector search underperforms on keyword-heavy queries, and how to combine it with BM25 using score fusion that actually works.
3 min read
Tag
Embeddings
6 articles
AI
Semantic Caching for LLM Cost Reduction
How semantic caching cuts LLM spend by reusing responses to meaningfully similar queries, and the correctness traps that come with it.
3 min read
AI
Vector Database Selection Criteria for 2026
The technical criteria that actually predict whether a vector database will hold up in production, beyond raw ANN benchmark numbers.
3 min read
AI
Choosing and Evaluating Embedding Models for Retrieval
How to pick an embedding model for your retrieval stack using benchmarks that actually correlate with your data, not just MTEB leaderboard rank.
3 min read
AI
RAG Architecture in Production: What Actually Breaks
A field guide to the parts of retrieval-augmented generation that fail under real traffic, real documents, and real users.
3 min read
Machine Learning
Embeddings, Explained With Minimal Math
What embeddings actually are, why distance in that space means something, and how to reason about them without wading through linear algebra.
3 min read